Sensor scheduling based on permissible consecutive observation loss

In this paper, we investigate the problem of scheduling multiple Kalman filters for multiple processes, where each process is observed by a Kalman filter and at each time step only one Kalman filter could obtain observation. The objective is to find a scheduling scheme such that the desired estimation qualities for all the processes could be satisfied. Two novel concepts, permissible consecutive observation loss (PCOL) and least consecutive observation (LCO), are introduced to characterize feasible observation sequences. Two methods, namely, threshold method and periodic method, are developed to calculate PCOL and LCO for a given desired estimation quality. Based on derived PCOL and LCO requirements, two efficient algorithms are presented to find a feasible observation sequence. Both rigorous analysis and simulation results are provided to validate the approaches.